CN115759727A - Electric power spot market risk early warning method, system, equipment and storage medium - Google Patents
Electric power spot market risk early warning method, system, equipment and storage medium Download PDFInfo
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Abstract
The invention provides a method, a system, equipment and a storage medium for electric power spot market risk early warning, wherein the method comprises the following steps: acquiring the day-ahead information of the electric power spot market; establishing a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model; obtaining a historical spot price fluctuation rate according to a GARCH model, and determining a market risk threshold according to the historical spot price fluctuation rate; according to the obtained electric power spot market information to be analyzed and the GARCH model, a spot price fluctuation rate predicted value is obtained; and carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result. The method and the system are based on the visualization analysis of the spot market risk, accurately and effectively predict the fluctuation of the spot price and the market risk caused by the fluctuation, are convenient for relevant departments and enterprises to take targeted measures in time, and ensure the safe and stable operation of the power system.
Description
Technical Field
The invention relates to the technical field of risk monitoring, in particular to a method and a system for electric power spot market risk early warning based on spot market fluctuation rate, computer equipment and a storage medium.
Background
The price of the electric power spot market is easy to fluctuate under the influence of various factors, and the fluctuation can directly influence the relevant changes of the market, so that the problems of insufficient coal supply, insufficient electric power supply and the like are caused, and the operation stability and safety of the whole electric power system are further influenced. Therefore, how to effectively predict the price fluctuation of the electric power spot market and perform corresponding market risk early warning becomes an important problem to be solved urgently.
However, the actual electric power spot price is mostly represented as a sequence with frequent fluctuation and instability, and cannot be effectively predicted directly through a common time sequence model (such as an autoregressive model), the obtained electric power spot price prediction result is often deviated from the actual value, the fluctuation of the spot price cannot be predicted accurately and reliably based on the electric power spot price prediction result, and corresponding market risk early warning is carried out, so that the actual application value is low.
Disclosure of Invention
The invention aims to provide an electric power spot market risk early warning method, which is characterized in that a GARCH model is established according to the characteristic that the spot price fluctuates frequently and unstably, the price risk in the spot market is detected by taking the spot price fluctuation rate as a research object and a risk reference index based on the GARCH model, the visualization analysis of the spot market risk is realized, the defects of the application of the prior art are effectively overcome, the market risk caused by the fluctuation and fluctuation of the spot price is accurately and effectively predicted, the reliable basis is provided for relevant departments and enterprises to take targeted measures in time, and the method has important practical significance.
In order to achieve the above objects, it is necessary to provide a method, a system, a computer device and a storage medium for electric power spot market risk early warning in view of the above technical problems.
In a first aspect, an embodiment of the present invention provides a risk early warning method for an electric power spot market, where the method includes the following steps:
acquiring the day-ahead information of the electric power spot market; the day-ahead information of the power spot market comprises a daily spot average price, a daily average market bidding space and a daily port coal price;
establishing a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model;
obtaining a historical spot price fluctuation rate according to the GARCH model, and determining a market risk threshold according to the historical spot price fluctuation rate;
according to the obtained electric power spot market information to be analyzed and the GARCH model, a spot price fluctuation rate predicted value is obtained;
and carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result.
Further, the step of establishing a GARCH model according to the day-ahead information of the power spot market includes:
determining the daily spot average price as an explained variable, and determining the daily average market bidding space and the daily port coal price as explained variables;
establishing the mean model according to the explained variable and the explaining variable;
and establishing a corresponding variance model according to the mean model, and obtaining the GARCH model according to the mean model and the variance model.
Further, the step of establishing the mean model according to the explained variable and the explained variable comprises:
carrying out stationarity test on the explained variable and the explaining variable, and carrying out difference processing on unstable sequence variables in the explained variable and the explaining variable to obtain a corresponding stable explained variable and a corresponding stable explaining variable;
and establishing the mean value model according to the stable explained variable and the stable explained variable.
Further, the GARCH model is represented as:
mean model: p = c + a 1 ×CECI+a 2 ×LOAD+u t
Variance model:
wherein P represents the daily spot average price; c. delta 0 Representing a constant term in the model; a is 1 、a 2 、δ i And gamma j Coefficients representing variables in the model; CECI and LOAD respectively represent daily port coal price and daily average bidding space; u. of t Representing the disturbance term, u, in the mean model t-i A perturbation term representing the lag i order, r represents u t Maximum hysteresis order of (d); sigma t 2 Represents u t Variance of (a) t-j 2 Represents u t The variance of the lag j order, s denotes σ t 2 The maximum hysteresis order of (c).
Further, the step of obtaining the historical spot price fluctuation rate according to the GARCH model includes:
and taking the variance of disturbance items in the mean value model as the fluctuation rate of the spot price, and obtaining the fluctuation rate of the historical spot price according to the day-ahead information of the electric power spot market.
Further, the step of determining a market risk threshold based on the historical spot price volatility includes:
sorting the fluctuation rates of the historical spot prices in a descending order, and drawing a corresponding probability accumulation graph;
determining risk accumulation probability corresponding to preset early warning levels, obtaining corresponding risk fluctuation rate data according to the risk accumulation probability and the probability accumulation graph, and taking the risk fluctuation rate data corresponding to each preset early warning level as a corresponding market risk threshold.
Further, the market risk threshold comprises a red early warning value, a yellow early warning value and a white early warning value;
the step of carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result comprises the following steps:
judging whether the spot price fluctuation rate predicted value is greater than the red early warning value, if so, judging that the risk early warning result is red early warning, otherwise, judging whether the spot price fluctuation rate predicted value is greater than the yellow early warning value;
if the spot price fluctuation rate predicted value is larger than the yellow early warning value, judging that the risk early warning result is yellow early warning, otherwise, judging whether the spot price fluctuation rate predicted value is larger than the white early warning value;
and if the spot price fluctuation rate predicted value is larger than the white early warning value, judging that the risk early warning result is a white early warning, otherwise, judging that the risk early warning result is risk-free.
In a second aspect, an embodiment of the present invention provides an electric power spot market risk early warning system, where the system includes:
the data acquisition module is used for acquiring the day-ahead information of the electric power spot market; the day-ahead information of the electric power spot market comprises a daily spot average price, a daily average market bidding space and a daily port coal price;
the model establishing module is used for establishing a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model;
the threshold value determining module is used for obtaining the historical spot price fluctuation rate according to the GARCH model and determining the market risk threshold value according to the historical spot price fluctuation rate;
the fluctuation rate prediction module is used for obtaining a fluctuation rate prediction value of the spot price according to the obtained electric power spot market information to be analyzed and the GARCH model;
and the risk early warning module is used for carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method when executing the computer program.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the steps of the above method.
The method realizes the technical scheme that based on the acquired day-ahead information of the electric power spot market including daily spot average price, daily average market bidding space and daily port coal price, a GARCH model including a mean value model and a variance model is established, a market risk threshold value is determined according to the historical spot price fluctuation rate obtained by the GARCH model, and after a spot price fluctuation rate predicted value is obtained according to the acquired electric power spot market information to be analyzed and the GARCH model, risk early warning is carried out on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value, and a corresponding risk early warning result is obtained. Compared with the prior art, the electric power spot market risk early warning method has the advantages that the GARCH model is established according to the characteristics of frequent and unstable spot price fluctuation, the spot price fluctuation rate is used as a research object and a risk reference index, the price risk in the spot market is detected accordingly, the visualization analysis of the spot market risk is realized, the market risk caused by the fluctuation and fluctuation of the spot price is accurately and effectively predicted, the pertinent departments and enterprises can take targeted measures in time, the safe and stable operation of an electric power system is guaranteed, and the electric power spot market risk early warning method has important practical significance and application value.
Drawings
FIG. 1 is a block diagram of a risk early warning in the electric power spot market in an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a risk early warning method for the electric power spot market according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a probability accumulation graph plotted against historical spot price volatility in an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a risk early warning system in a power spot market according to an embodiment of the present invention;
fig. 5 is an internal structural diagram of a computer device in the embodiment of the present invention.
Detailed Description
In order to make the purpose, technical solution and advantages of the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments, and it is obvious that the embodiments described below are part of the embodiments of the present invention, and are used for illustrating the present invention only, but not for limiting the scope of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The electric power spot market risk early warning method provided by the invention mainly considers the problems that the electric power spot market price with frequent fluctuation and unstable sequence is difficult to accurately predict by adopting the existing time sequence model, and the effective market risk early warning analysis can not be carried out based on the predicted value of the electric power spot market price, so that the safe and stable operation of an electric power system can not be ensured, provides a GARCH model based on the characteristics of frequent fluctuation and instability of the spot price as shown in the frame of figure 1, and uses the spot price fluctuation rate as a research object and a risk reference index to detect the price risk in the spot market according to the above, thereby realizing the technical scheme of imaging analysis of the spot market risk, really realizing the accurate and effective prediction of the market risk caused by the fluctuation and fluctuation of the spot price, and timely providing a reliable basis for making targeted measures for related departments and enterprises; the following embodiments will explain the electric power spot market risk early warning method of the present invention in detail.
In one embodiment, as shown in fig. 2, there is provided a power spot market risk early warning method, including the following steps:
s11, acquiring day-ahead information of the electric power spot market; the day-ahead information of the electric power spot market can be understood as related operation information of the electric power spot market in the past period of time, which is acquired based on application needs, including but not limited to daily spot average price, daily average market bidding space and daily port coal price, the corresponding daily spot average price can be understood as an average value of daily spot prices of various nodes in the whole electric power market, and the daily average market bidding space can be understood as daily electric power capacity used for quotation of the whole electric power market; it should be noted that, in the embodiment, the day-ahead information of the electric power spot market is used as a modeling basis of a subsequent GARCH model for spot price fluctuation prediction and market risk analysis, and any method capable of effectively acquiring the required information including the above information may be adopted as the corresponding acquiring method, which is not specifically limited herein;
s12, establishing a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model; the GARCH model can be understood as a mean value model established based on the day-ahead information of the electric power spot market, and then a difference value between a real value and a predicted value of a spot average price in the mean value model is used for modeling analysis to obtain a generalized autoregressive conditional variance model capable of reflecting the change and fluctuation conditions of various research variables;
specifically, the step of establishing a GARCH model according to the day-ahead information of the electric power spot market includes:
determining the daily spot average price as an explained variable, and determining the daily average market bidding space and the daily port coal price as explained variables;
establishing the mean model according to the explained variable and the explained variable; the mean model can be established in principle directly according to the acquired daily stock average price, daily average market bidding space and daily port coal price, and considering that the acquired daily stock average price, daily average market bidding space and daily port coal price are time sequence variables and are easy to have instability which affects modeling reliability; in order to improve the reliability and the application accuracy of the mean model, in this embodiment, before the mean model is built by using the determined explanatory variables and the explained variables, the following method is preferably adopted to perform stationarity analysis processing on the explained variables and each explanatory variable to obtain a variable sequence that ensures the modeling accuracy.
Specifically, the step of establishing the mean model according to the explained variable and the explained variable includes:
carrying out stationarity test on the explained variable and the explaining variable, and carrying out difference processing on unstable sequence variables in the explained variable and the explaining variable to obtain a corresponding stable explained variable and a corresponding stable explaining variable;
and establishing the mean value model according to the stable explained variable and the stable explained variable.
It should be noted that the above-mentioned stationarity check may be understood as a time series stationarity check, and may adopt a unit root check or an ADF check, and the corresponding difference processing may also be understood as a difference for a non-stationary time series, and the method of the stationarity check and the non-stationary sequence variable difference processing is not particularly limited herein.
Establishing a corresponding variance model according to the mean model, and obtaining the GARCH model according to the mean model and the variance model; wherein, the GARCH model is expressed as:
mean model: p = c + a 1 ×CECI+a 2 ×LOAD+u t
Variance model:
wherein P represents the daily spot average price; c. delta. For the preparation of a coating 0 Representing a constant term in the model; a is 1 、a 2 、δ i And gamma j Coefficients representing variables in the model; CECI and LOAD respectively represents daily port coal price and daily average bidding space; u. of t Representing the disturbance term, u, in the mean model t-i A perturbation term representing the lag i order, r represents u t Maximum hysteresis order of (d); sigma t 2 Represents u t Variance of (a) t-j 2 Represents u t The variance of the lag j order, s denotes σ t 2 The maximum hysteresis order of (c).
S13, obtaining a historical spot price fluctuation rate according to the GARCH model, and determining a market risk threshold according to the historical spot price fluctuation rate; the variance model in the GARCH model is a model established by taking the variance of a disturbance item in the mean model as an interpreted variable, and because the interpreted variable in the mean model is the spot price, the variance of the disturbance item in the mean model can be used as the fluctuation rate for researching the fluctuation of the spot price, and the corresponding variance model is used as a prediction model of the fluctuation rate of the spot price for carrying out spot price fluctuation analysis and corresponding market risk early warning;
specifically, the step of obtaining the historical spot price fluctuation rate according to the GARCH model includes:
taking the variance of disturbance items in the mean value model as spot price fluctuation rate, and obtaining the historical spot price fluctuation rate according to the day-ahead information of the electric power spot market; that is, the variance model in the obtained GARCH model is used as the spot price fluctuation prediction model, the collected current power market information before day is input to obtain the corresponding historical spot price fluctuation rate, and the probability statistical analysis is performed by the following method based on the obtained historical spot price fluctuation rate to determine a reasonable and effective market risk threshold.
Specifically, the step of determining a market risk threshold according to the historical spot price fluctuation rate includes:
sorting the fluctuation rates of the historical spot prices in a descending order, and drawing a corresponding probability accumulation graph; the probability accumulation graph is shown in fig. 3, and represents a probability value corresponding to the fact that the spot price fluctuation rate is smaller than a certain value in the historical data by taking the spot price fluctuation rate as an abscissa and the accumulated probability as an ordinate;
determining risk accumulation probability corresponding to preset early warning levels, obtaining corresponding risk fluctuation rate data according to the risk accumulation probability and the probability accumulation graph, and taking the risk fluctuation rate data corresponding to each preset early warning level as a corresponding market risk threshold; the risk cumulative probability can be understood as a cumulative probability value corresponding to different early warning levels determined according to market risk analysis requirements, and the determination method of the cumulative probability value can be selected according to actual application requirements, and is not particularly limited; after the risk accumulation probability corresponding to the early warning level is determined, corresponding risk fluctuation rate data can be determined according to the corresponding probability accumulation graph and used as market risk threshold values for subsequently identifying different early warning levels.
S14, obtaining a spot price fluctuation rate predicted value according to the obtained electric power spot market information to be analyzed and the GARCH model; the specific process is the same as the method for acquiring the historical spot price fluctuation rate, and reference can be made to the above description, and details are not repeated here.
S15, performing risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result; the market risk threshold values correspond to the corresponding early warning levels one to one as described above, the division of the specific market risk threshold values can be adjusted in principle according to actual application requirements, and the embodiment preferably divides the early warning levels into four levels according to the severity of the risk: assuming that the risk accumulation probabilities corresponding to the red early warning, the yellow early warning, the white early warning and the no risk are respectively 90% -100%, 80% -90%, 70% -80% and 0-70%, the corresponding market risk threshold values comprise a red early warning value, a yellow early warning value and a white early warning value, the red early warning value corresponds to the risk fluctuation rate data with the risk accumulation probability of 90% -100%, the yellow early warning value corresponds to the risk fluctuation rate data with the risk accumulation probability of 80% -90%, and the white early warning corresponds to the risk fluctuation rate data with the risk accumulation probability of 70% -80%; the red early warning represents a high risk range, and the spot price fluctuates violently, so that the market and the operation of a power system are seriously influenced; yellow early warning represents a moderate risk range, the fluctuation of spot prices is obvious, and the market and the operation of a power system are greatly influenced; the white early warning represents a risk concern range, the fluctuation of spot prices is obvious, and slight influence is generated on the market and the operation of a power system.
Specifically, the step of performing risk early warning on the electric power spot market according to the market risk threshold and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result includes:
judging whether the spot price fluctuation rate predicted value is greater than the red early warning value, if so, judging that the risk early warning result is red early warning, otherwise, judging whether the spot price fluctuation rate predicted value is greater than the yellow early warning value;
if the spot price fluctuation rate predicted value is larger than the yellow early warning value, judging that the risk early warning result is yellow early warning, otherwise, judging whether the spot price fluctuation rate predicted value is larger than the white early warning value;
if the spot price fluctuation rate predicted value is larger than the white early warning value, judging that the risk early warning result is a white early warning, otherwise, judging that the risk early warning result is risk-free;
the method can realize accurate prediction of spot price fluctuation, and meanwhile, effective spot market risk early warning is carried out based on a spot price fluctuation predicted value, market risk possibly caused by spot price fluctuation is reasonably and reliably evaluated, and a corresponding risk early warning result is obtained to be displayed and issued, so that relevant departments and relevant enterprises carry out corresponding plan making and preparation of coping measures for market change caused by spot price fluctuation, and the system is used for avoiding the market risk and carrying out corresponding adjustment.
According to the method, the GARCH model comprising the mean value model and the variance model is established according to the acquired day-ahead information of the electric power spot market comprising the daily spot average price, the daily average market bidding space and the daily port coal price, the market risk threshold is determined according to the historical spot price fluctuation rate obtained by the GARCH model, the corresponding risk early warning result is obtained according to the acquired electric power spot market information to be analyzed and the GARCH model after the spot price fluctuation rate predicted value is obtained, the risk early warning is carried out on the electric power spot market according to the market risk threshold and the spot price fluctuation rate predicted value, the spot price risk and the spot market risk are represented by the spot price fluctuation rate based on the GARCH model, the image analysis of the spot market risk is realized, the fluctuation of the spot price and the market risk caused by the fluctuation can be accurately and effectively predicted, the important reliable assessment and early warning of the electric power spot market risk are facilitated, and powerful bases are provided for relevant departments and enterprises to take targeted measures in time, the safe and stable operation of the electric power system, and the important significance and the application value of the guarantee are achieved.
In one embodiment, as shown in fig. 4, there is provided an electric power spot market risk early warning system, the system comprising:
the data acquisition module 1 is used for acquiring the day-ahead information of the electric power spot market; the day-ahead information of the power spot market comprises a daily spot average price, a daily average market bidding space and a daily port coal price;
the model establishing module 2 is used for establishing a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model;
the threshold value determining module 3 is used for obtaining the historical spot price fluctuation rate according to the GARCH model and determining the market risk threshold value according to the historical spot price fluctuation rate;
the fluctuation rate prediction module 4 is used for obtaining a fluctuation rate prediction value of the spot price according to the obtained electric power spot market information to be analyzed and the GARCH model;
and the risk early warning module 5 is used for carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result.
For specific limitations of the electric power spot market risk early warning system, reference may be made to the above limitations of an electric power spot market risk early warning method, which is not described herein again. All or part of the modules in the electric power spot market risk early warning system can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Fig. 5 shows an internal structure diagram of a computer device in one embodiment, and the computer device may be specifically a terminal or a server. As shown in fig. 5, the computer apparatus includes a processor, a memory, a network interface, a display, and an input device, which are connected through a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a power spot market risk early warning method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those of ordinary skill in the art that the architecture shown in FIG. 5 is a block diagram of only a portion of the architecture associated with the subject application, and is not intended to limit the computing devices to which the subject application may be applied, as a particular computing device may include more or less components than those shown, or may combine certain components, or have a similar arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the steps of the above method being performed when the computer program is executed by the processor.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
In summary, the present invention provides a method, a system, a computer device and a storage medium for early warning of risk in a power spot market, which implements a GARCH model including a mean value model and a variance model based on acquired day-ahead information of the power spot market including daily spot average price, daily average market bidding space and daily port coal price, and determines a market risk threshold according to historical spot price fluctuation rate obtained by the GARCH model, and a technical scheme for obtaining a corresponding risk early warning result according to the acquired to-be-analyzed power spot market information and the GARCH model after obtaining a spot price fluctuation rate predicted value, and then performs risk early warning on the power spot market according to the market risk threshold and the spot price fluctuation rate predicted value.
The embodiments in this specification are described in a progressive manner, and all the same or similar parts of the embodiments are directly referred to each other, and each embodiment is described with emphasis on differences from other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. It should be noted that, the technical features of the embodiments may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express some preferred embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various modifications and substitutions can be made without departing from the technical principle of the present invention, and these should be construed as the protection scope of the present application. Therefore, the protection scope of the present patent application shall be subject to the protection scope of the claims.
Claims (10)
1. A risk early warning method for a power spot market is characterized by comprising the following steps:
acquiring the day-ahead information of the electric power spot market; the day-ahead information of the power spot market comprises a daily spot average price, a daily average market bidding space and a daily port coal price;
establishing a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model;
obtaining a historical spot price fluctuation rate according to the GARCH model, and determining a market risk threshold according to the historical spot price fluctuation rate;
according to the obtained electric power spot market information to be analyzed and the GARCH model, a spot price fluctuation rate predicted value is obtained;
and carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result.
2. The electric power spot market risk early warning method according to claim 1, wherein the step of building a GARCH model according to the electric power spot market day-ahead information comprises:
determining the daily spot average price as an explained variable, and determining the daily average market bidding space and the daily port coal price as explained variables;
establishing the mean model according to the explained variable and the explained variable;
and establishing a corresponding variance model according to the mean model, and obtaining the GARCH model according to the mean model and the variance model.
3. The power spot market risk warning method of claim 2, wherein the step of building the mean model from the interpreted variables and the explanatory variables comprises:
carrying out stationarity test on the explained variable and the explaining variable, and carrying out difference processing on unstable sequence variables in the explained variable and the explaining variable to obtain a corresponding stable explained variable and a corresponding stable explaining variable;
and establishing the mean value model according to the stable explained variable and the stable explained variable.
4. The power spot market risk early warning method of claim 2, wherein the GARCH model is represented as:
mean model: p = c + a 1 ×CECI+a 2 ×LOAD+u t
Variance model:
wherein, P represents the average daily stock price; c. delta 0 Representing a constant term in the model; a is 1 、a 2 、δ i And gamma j Coefficients representing variables in the model; CECI and LOAD respectively represent daily port coal price and daily average bidding space; u. of t Representing the disturbance term, u, in the mean model t-i A perturbation term representing the lag i order, r represents u t The maximum hysteresis order of (d); sigma t 2 Represents u t Variance of (a) t-j 2 Represents u t The variance of the lag j order, s denotes σ t 2 The maximum hysteresis order of (c).
5. The electric power spot market risk warning method of claim 1, wherein the step of deriving a historical spot price volatility according to the GARCH model comprises:
and taking the variance of disturbance items in the mean value model as the fluctuation rate of the spot price, and obtaining the fluctuation rate of the historical spot price according to the day-ahead information of the electric power spot market.
6. The power spot market risk warning method of claim 1, wherein the determining a market risk threshold based on the historical spot price volatility comprises:
sorting the fluctuation rates of the historical spot prices in a descending order, and drawing a corresponding probability accumulation graph;
determining risk accumulation probability corresponding to preset early warning levels, obtaining corresponding risk fluctuation rate data according to the risk accumulation probability and the probability accumulation graph, and taking the risk fluctuation rate data corresponding to each preset early warning level as a corresponding market risk threshold.
7. The power spot market risk early warning method of claim 1, wherein the market risk threshold comprises a red early warning value, a yellow early warning value, and a white early warning value;
the step of carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result comprises the following steps:
judging whether the spot price fluctuation rate predicted value is greater than the red early warning value, if so, judging that the risk early warning result is red early warning, otherwise, judging whether the spot price fluctuation rate predicted value is greater than the yellow early warning value;
if the spot price fluctuation rate predicted value is larger than the yellow early warning value, judging that the risk early warning result is yellow early warning, otherwise, judging whether the spot price fluctuation rate predicted value is larger than the white early warning value;
and if the predicted value of the spot price fluctuation rate is greater than the white early warning value, judging that the risk early warning result is a white early warning, otherwise, judging that the risk early warning result is risk-free.
8. An electric power spot market risk early warning system, the system comprising:
the data acquisition module is used for acquiring the day-ahead information of the electric power spot market; the day-ahead information of the electric power spot market comprises a daily spot average price, a daily average market bidding space and a daily port coal price;
the model building module is used for building a GARCH model according to the day-ahead information of the electric power spot market; the GARCH model comprises a mean model and a variance model;
the threshold value determining module is used for obtaining the historical spot price fluctuation rate according to the GARCH model and determining a market risk threshold value according to the historical spot price fluctuation rate;
the fluctuation rate prediction module is used for obtaining a fluctuation rate prediction value of the spot price according to the obtained electric power spot market information to be analyzed and the GARCH model;
and the risk early warning module is used for carrying out risk early warning on the electric power spot market according to the market risk threshold value and the spot price fluctuation rate predicted value to obtain a corresponding risk early warning result.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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